Some of the pricing seems very optimistic on Airdna for the areas I'm looking at, compared with what I'm actually seeing on Airbnb. Do all of you experienced STR'ers find their data reliable? I'm mostly concerned with accurate occupancy rates.
Hi Julia Ann,
I am currently utilizing Airdna's market minder tool and would like to converse with some other users of their data. I do find their data to be relatively accurate, maybe a 5% variance between my actual performance and what they report. Can we connect and discuss further? I'll send you a PM now.
I'm curious too. I am currently using it to gauge income on potential purchase and also worry that it's optimistic....
I have two units in the same building on Airbnb. On AirDNA, one's annual revenue is shown accurately, but the other, larger property's annual revenue is shown as a sum of both units. I have emailed AirDNA about this and they basically said that's not how the site works. I said, I know how much I make.
That being said, if you can identify single-property owners in your map area, it seems to provide a fairly decent picture of what they are earning. I think occupancy rates are way off, however, because they do not account for personal time you block off for yourself or others as opposed to actual rental dates.
I find it very inaccurate.
Airbnb doesn't collect taxes so hosts like myself typically charge higher nightly rates than on VRBO to offset it. So nightly rates are artificially inflated.
One of my condos in Kauai is a "top 10" performing condo according to airdna. 85% of my rentals are from VRBO and I have zero idea how the stats on that listing are made but it's way off from reality.
I looked at it once and found it pretty worthless. Just another way to get paralysis. Find a property similar to what you're looking for and study the calendar.
@Lucas Carl I think you're right about studying individual comps as the best way to analyze a property or area. The reason being is, owners know their comps better than anyone else. However, there are a few complexities to be aware of when manually tracking data through an Airbnb/Homeaway/Vrbo room calendar.
1. When looking at Airbnb/Homeaway/Vrbo, the room calendar you see might not actually reflect the current blocks/bookings because of minimum stay requirements. For example, if a booking exists from Oct 1-4 and another booking is made from Oct 6-9 and the minimum stay is 3 nights, Oct 5-6 will appear as if it has been booked/blocked because the minimum stay requirement can't be met for the span. If you calculate all days (Oct 1-9) as revenue days, you'll be off by 2 days ( > 20% inaccurate) .
2. While changes in booked days are the most important, since these translate to revenue, changes to price are also part of the journey and shouldn't be ignored. How do changes in daily price affect occupancy (or overall revenue) for comps?
3. Manually tracking all of this data is hard and it requires dedication to do it every day. Looking at recording a years worth of data for one Airbnb/Homeaway/Vrbo room (365 days from today), every day for 30 days means: 30 days * 365 days of data * 2 data points (price and availability) = 21,900 values ... and that's just doing it for one month. A year is 21,900 values * 12 months = 262,800 values. To improve your idea of how an area is performing, you probably want to use more comps, let's say 5, that means 262,800 values * 5 comps = 1,314,000 values.
Updated 2 months ago
For #1, I meant nights of the 4th,5th would appear as booked/blocked (not the 5th/6th).
Updated 8 months ago
For #1, I meant nights of the 4th,5th would appear as booked/blocked (not the 5th/6th).
@Lucas Carl - Agree. They have a ton of information on there (and that's great) but it's hard to pick and choose what's truly useful versus what is not. It's good to know 1.) how many places around you are renting; 2.) how many are available tomorrow v. a six weeks out; 3.) what the rate is for your property size and if there's seasonal variance. Those are the basics that help people get started and needed to make a confident decision.
One thing to add to @Alan DC, when looking at calendars you're limited to owner managed. Property managers frequently leave calenders empty even when they're in fact, full. That way they field the inquiries for the property and try to sell them on another unit. Its really annoying but I understand why they do it.
@Mike V. Can calendars be left open while "book now" is enabled? If so, I don't think this would be a problem for selecting a comp, because rental occupancy needs to look correct in order to select a good rental comp.
Originally posted by @Alan DC:
@Mike Verna Can calendars be left open while "book now" is enabled? If so, I don't think this would be a problem for selecting a comp, because rental occupancy needs to look correct in order to select a good rental comp.
If they enable book now then the calender's should be updated. I just did a quick search of my target market and did notice that they don't generally have the book now enabled. I searched 3 bedrooms in a very tight area and it went from 65 to 33 when I filtered by 'Instant confirmation' Very good observation! You can probably select the instant confirmation to filter out the property managers.
Side note: I did the same search but filtered by "owner managed" and it only dropped to 54. Found several tagged owner managed that are actually property managers.
I also went back through my airdna stats and tried to backdoor into the numbers and still for the life of me cant even get close to what theyre telling me my unit is.
It's very easy to understand why airdna is ridiculously inaccurate:
They use the airbnb API with data only from airbnb.
I would consider 95% of serious STR hosts are at least on one other platform such as VRBO. Their data is incomplete by a huge amount.
When using airdna's data we look at every single comparable separately. Some properties are about right, some properties are way off because of blocked calendars or other other issues. If you validate and cull the Airdna data to exclude properties that are likely o have inaccurate data, I ind it helpful. If a competitive property on airdna has months blocked out on the calendar, or has a super low response rate, simply toss it from the data set you are looking at.
I personally think Airdna is filled with false information. I was at a meetup in my area this week and I told a guy where I was investing and he told me that Airdna told him that I was investing in a bad spot for AirBnB. Now personally I'm glad AirDNA is giving out these false reports because of course that's more money for me but the area that I invest in is an obvious hot spot for Airbnb. I'm very curious to how AirDNA runs it's numbers. Airbnb is still up and coming how are they polling all of this information and know the good and bad spots? If they are just grabbing information from cities with rentals then I think it can be quite accurate but if there are cities with few hosts then how would AirDNA be reliable to tell you if it's a bad area or not. I have a one spot that's been doing great for me for the past 3 months and AirDNA's numbers on it are worthless because there aren't many listings in the area therefore they are dishing out false reports. That's just my two cents.
I would say not reliable in the slightest,
I used Airdna for all of 15 minutes before realizing that it wasn’t what I expected, and not to mention that Airdna has some of the worst customer service I have ever seen. I tried their product on the trust of their 7-day money back garuantee, spent no more than 15 minutes on the site and requested a refund, weeks have gone buy and still to this day they will not honor their 7-day money back garuntee. I would never do business them.
I subscribed to an AirDNA report for my city. Under "Top Properties," I entered by my Airbnb specs - my home came up at the #1 Top Property! It showed that I'd earned $46,000 in annual revenue and that I was 94% booked. Unfortunately, most of that 'booked' time was actually blocked, and my actual revenue was more like $6,000. It was very disappointing as I've been trying to find a source for info of this kind for a while, and I thought I'd found it, but that error on my home was a HUGE red flag. I cancelled my subscriptions immediately. We'll see if I get the full refund since I just subscribed a few days ago...
I researched my city, and their data was spot on with the results of my STRs. That's when I realized that only my STRs comprised the data set for AirdNAY. So of course the results would seem 100% correct, they are just using my data for their results.
That was the first and last time I went to the AirdNAY.
Airdna is either super wrong or has unstated assumptions. Every listing on Airdna has the following info...
1) Annual Revenue
2) Occupancy Rate
3) Average Daily Rate
You would expect Annual Revenue = Occupancy Rate * Average Daily Rate.
However this is almost never true and technically Airdna is including cleaning fees in the revenue! (should make it higher)
For example (and this is not an outlier) Revenue = ~$20k, Occupancy = 75%, and average daily rate = $110.
$110*75%*365 = $30k estimated revenue.
Listed revenue is $20k. This is a $10k+ disconnect.
The basic stats seem wrong. Am I missing something?
Their figures get you in the ballpark. It might be in the ballpark that is in the next state over, or another ballpark 500 miles away.
Take it with a grain of salt. Deflate their numbers by 50% and you probably have a realistic number of what can be expected.
Personally, I look at the local motels. Look at the number of cars in the lot and find out how much they charge a night. I sorta crunch those numbers and charge $400 a week for a 2 bedroom furnished house with a washer/dryer, cable/wifi/Netflix and full kitchen. A local motel is also $400.
Love that @Alan Da Costa
Great point. I am brand new to this. Coming from a large organization (totally different field) where I had lots of tools to rely on...what tools should I then start with to analyze properties?
Airdna has definitely not been accurate in my experience. When I ran my current listings through it, It was consistently low, some by 40% or more others by less. Multiple listings in multiple states. Hope this helps.
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